{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# LIME to Inspect Image & Text Classification "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "This tutorial focuses on showing how to use Captum's implementation of Local Interpretable Model-agnostic Explanations (LIME) to understand neural models. The following content is divided into an image classification section to present our high-level interface `Lime` class and a text classification section for the more customizable low-level interface `LimeBase`. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import torch\n",
    "import torch.nn.functional as F\n",
    "\n",
    "from captum.attr import visualization as viz\n",
    "from captum.attr import Lime, LimeBase\n",
    "from captum._utils.models.linear_model import SkLearnLinearRegression, SkLearnLasso\n",
    "\n",
    "import os\n",
    "import json"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 1. Image Classification"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "In this section, we will learn applying Lime to analyze a Resnet trained on ImageNet-1k. For testing data, we use samples from PASCAL VOC 2012 since its segmentation masks can directly serve as semantic \"super-pixels\" for images. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "from torchvision.models import resnet18\n",
    "from torchvision.datasets import VOCSegmentation\n",
    "import torchvision.transforms as T\n",
    "from captum.attr._core.lime import get_exp_kernel_similarity_function\n",
    "\n",
    "from PIL import Image\n",
    "import matplotlib.pyplot as plt"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 1.1 Load the model and dataset"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We can directly load the pretrained Resnet from torchvision and set it to evaluation mode as our target image classifier to inspect. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "resnet = resnet18(pretrained=True)\n",
    "resnet = resnet.eval()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "This model predicts ImageNet-1k labels for given sample images. To better present the results, we also load the mapping of label index and text."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "--2021-06-30 17:05:03--  https://s3.amazonaws.com/deep-learning-models/image-models/imagenet_class_index.json\n",
      "Resolving fwdproxy (fwdproxy)... 2401:db00:21ff:ff2f:face:b00c:0:1e10\n",
      "Connecting to fwdproxy (fwdproxy)|2401:db00:21ff:ff2f:face:b00c:0:1e10|:8080... connected.\n",
      "Proxy request sent, awaiting response... 200 OK\n",
      "Length: 35363 (35K) [application/octet-stream]\n",
      "Saving to: ‘/home/aoboyang/.torch/models/imagenet_class_index.json.38’\n",
      "\n",
      "imagenet_class_inde 100%[===================>]  34.53K  --.-KB/s    in 0.02s   \n",
      "\n",
      "2021-06-30 17:05:03 (2.13 MB/s) - ‘/home/aoboyang/.torch/models/imagenet_class_index.json.38’ saved [35363/35363]\n",
      "\n"
     ]
    }
   ],
   "source": [
    "!wget -P $HOME/.torch/models https://s3.amazonaws.com/deep-learning-models/image-models/imagenet_class_index.json"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "labels_path = os.getenv('HOME') + '/.torch/models/imagenet_class_index.json'\n",
    "with open(labels_path) as json_data:\n",
    "    idx_to_labels = {idx: label for idx, [_, label] in json.load(json_data).items()}"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "As mentioned before, we will use PASCAL VOC 2012 as the test data, which is available in torchvision as well. We will load it with `torchvision` transforms which convert both the images and targets, i.e., segmentation masks, to tensors."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "voc_ds = VOCSegmentation(\n",
    "    './VOC',\n",
    "    year='2012',\n",
    "    image_set='train',\n",
    "    download=False,\n",
    "    transform=T.Compose([\n",
    "        T.ToTensor(),\n",
    "        T.Normalize(\n",
    "            mean=[0.485, 0.456, 0.406],\n",
    "            std=[0.229, 0.224, 0.225]\n",
    "        )    \n",
    "    ]),\n",
    "    target_transform=T.Lambda(\n",
    "        lambda p: torch.tensor(p.getdata()).view(1, p.size[1], p.size[0])\n",
    "    )\n",
    ")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "This dataset provides an additional segmentation mask along with every image. Compared with inspecting each pixel, the segments (or \"super-pixels\") are semantically more intuitive for humans to perceive. We will discuss more in section 1.3.\n",
    "\n",
    "Let's pick one example to see how the image and corresponding mask look like. Here we choose an image with more than one segment besides the background, so that we can compare each segment's impact on the classification."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 921.6x345.6 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "sample_idx = 439\n",
    "\n",
    "def show_image(ind): \n",
    "    fig, ax = plt.subplots(1, 2, figsize=[6.4 * 2, 4.8])\n",
    "    for i, (name, source) in enumerate(zip(['Image', 'Mask'], [voc_ds.images, voc_ds.masks])):\n",
    "        ax[i].imshow(Image.open(source[ind]));\n",
    "        ax[i].set_title(f\"{name} {ind}\")\n",
    "        ax[i].axis('off')\n",
    "\n",
    "show_image(sample_idx)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 1.2 Baseline classification"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We can check how well our model works with the above example. The original Resnet only gives the logits of labels, so we will add a softmax layer to normalize them into probabilities. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "img, seg_mask = voc_ds[sample_idx]  # tensors of shape (channel, hight, width)\n",
    "\n",
    "outputs = resnet(img.unsqueeze(0))\n",
    "output_probs = F.softmax(outputs, dim=1).squeeze(0)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Then we present the top 5 predicted labels to verify the result."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "television (851): 0.083\n",
      "screen (782): 0.0741\n",
      "monitor (664): 0.0619\n",
      "laptop (620): 0.0421\n",
      "ashcan (412): 0.03\n"
     ]
    }
   ],
   "source": [
    "def print_result(probs, topk=1):\n",
    "    probs, label_indices = torch.topk(probs, topk)\n",
    "    probs = probs.tolist()\n",
    "    label_indices = label_indices.tolist()\n",
    "    for prob, idx in zip(probs, label_indices):\n",
    "        label = idx_to_labels[str(idx)]\n",
    "        print(f'{label} ({idx}):', round(prob, 4))\n",
    "        \n",
    "print_result(output_probs, topk=5)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "As we can see, the result is pretty reasonable."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 1.3 Inspect the model prediction with Lime"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "In this section, we will bring in LIME from Captum to analyze how the Resnet made the above prediction based on the sample image.\n",
    "\n",
    "Like many other Captum algorithms, Lime also supports analyzing a number of input features together as a group. This is very useful when dealing with images, where each color channel in each pixel is an input feature. Such a group is also refered as \"super-pixel\". To define our desired groups over input features, all we need is to provide a feature mask.\n",
    "\n",
    "In case of an image input, the feature mask is a 2D image of the same size, where each pixel in the mask indicates the feature group it belongs to via an integer value. Pixels of the same value define a group.\n",
    "\n",
    "This means we can readily use VOC's segmentation masks as feature masks for Captum! However, while segmentaion numbers range from 0 to 255, Captum prefers consecutive group IDs for efficiency. Therefore, we will also include extra steps to convert mask IDs."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Segmentation IDs: [0, 9, 20, 255]\n",
      "Feature mask IDs: [0, 1, 2, 3]\n"
     ]
    }
   ],
   "source": [
    "seg_ids = sorted(seg_mask.unique().tolist())\n",
    "print('Segmentation IDs:', seg_ids)\n",
    "\n",
    "# map segment IDs to feature group IDs\n",
    "feature_mask = seg_mask.clone()\n",
    "for i, seg_id in enumerate(seg_ids):\n",
    "    feature_mask[feature_mask == seg_id] = i\n",
    "    \n",
    "print('Feature mask IDs:', feature_mask.unique().tolist())"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "It is time to configure our Lime algorithm. Essentially, Lime trains an interpretable surrogate model to simulate the target model's predictions. So, building an appropriate interpretable model is the most critical step in Lime. Fortunately, Captum has provided many of the most common interpretable models to save the efforts. We will demonstrate the usages of Linear Regression and Linear Lasso. Another important factor is the similarity function. Because Lime aims to explain the local behavior of an example, it will reweight the training samples according to their similarity distances. By default, Captum's Lime uses the exponential kernel on top of the cosine distance. We will change to Euclidean distance instead which is more popular in vision. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [],
   "source": [
    "exp_eucl_distance = get_exp_kernel_similarity_function('euclidean', kernel_width=1000)\n",
    "\n",
    "lr_lime = Lime(\n",
    "    resnet, \n",
    "    interpretable_model=SkLearnLinearRegression(),  # build-in wrapped sklearn Linear Regression\n",
    "    similarity_func=exp_eucl_distance\n",
    ")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Next, we will analyze these groups' influence on the most confident prediction `television`. Every time we call Lime's `attribute` function, an interpretable model is trained around the given input, so unlike many other Captum's attribution algorithms, it is strongly recommended to only provide a single example as input (tensors with first dimension or batch size = 1). There are advanced use cases of passing batched inputs. Interested readers can check the [documentation](https://captum.ai/api/lime.html) for details.\n",
    "\n",
    "In order to train the interpretable model, we need to specify enough training data through the argument `n_samples`. Lime creates the perturbed samples in the form of interpretable representation, i.e., a binary vector indicating the “presence” or “absence” of features. Lime needs to keep calling the target model to get the labels/values for all perturbed samples. This process can be quite time-consuming depending on the complexity of the target model and the number of samples. Setting the `perturbations_per_eval` can batch multiple samples in one forward pass to shorten the process as long as your machine still has capacity. You may also consider turning on the flag `show_progress` to display a progess bar showing how many forward calls are left."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Lime attribution: 100%|██████████| 3/3 [00:08<00:00,  2.95s/it]\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Attribution range: -0.4122844636440277 to 2.849794864654541\n"
     ]
    }
   ],
   "source": [
    "label_idx = output_probs.argmax().unsqueeze(0)\n",
    "attrs = lr_lime.attribute(\n",
    "    img.unsqueeze(0),\n",
    "    target=label_idx,\n",
    "    feature_mask=feature_mask.unsqueeze(0),\n",
    "    n_samples=40,\n",
    "    perturbations_per_eval=16,\n",
    "    show_progress=True\n",
    ").squeeze(0)\n",
    "\n",
    "print('Attribution range:', attrs.min().item(), 'to', attrs.max().item())"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Now, let us use Captum's visualization tool to view the attribution heat map."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x432 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "def show_attr(attr_map):\n",
    "    viz.visualize_image_attr(\n",
    "        attr_map.permute(1, 2, 0).numpy(),  # adjust shape to height, width, channels \n",
    "        method='heat_map',\n",
    "        sign='all',\n",
    "        show_colorbar=True\n",
    "    )\n",
    "    \n",
    "show_attr(attrs)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The result looks decent: the television segment does demonstrate strongest positive correlation with the prediction, while the chairs have relatively trivial impact and the border slightly shows negative contribution.\n",
    "\n",
    "However, we can further improve this result. One desired characteristic of interpretability is the ease for humans to comprehend. We should help reduce the noisy interference and emphisze the real influential features. In our case, all features more or less show some influences. Adding lasso regularization to the interpretable model can effectively help us filter them. Therefore, let us try Linear Lasso with a fit coefficient `alpha`. For all built-in sklearn wrapper models, you can directly pass any sklearn supported arguments.\n",
    "\n",
    "Moreover, since our example only has 4 segments, there are just 16 possible combinations of interpretable representations in total. So we can exhaust them instead of random sampling. The `Lime` class's argument `perturb_func` allows us to pass a generator function yielding samples. We will create the generator function iterating the combinations and set the `n_samples` to its exact length."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Lime attribution: 100%|██████████| 1/1 [00:02<00:00,  2.51s/it]\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Attribution range: -0.047024477273225784 to 2.532824993133545\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x432 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "n_interpret_features = len(seg_ids)\n",
    "\n",
    "def iter_combinations(*args, **kwargs):\n",
    "    for i in range(2 ** n_interpret_features):\n",
    "        yield torch.tensor([int(d) for d in bin(i)[2:].zfill(n_interpret_features)]).unsqueeze(0)\n",
    "    \n",
    "lasso_lime = Lime(\n",
    "    resnet, \n",
    "    interpretable_model=SkLearnLasso(alpha=0.08),\n",
    "    similarity_func=exp_eucl_distance,\n",
    "    perturb_func=iter_combinations\n",
    ")\n",
    "\n",
    "attrs = lasso_lime.attribute(\n",
    "    img.unsqueeze(0),\n",
    "    target=label_idx,\n",
    "    feature_mask=feature_mask.unsqueeze(0),\n",
    "    n_samples=2 ** n_interpret_features,\n",
    "    perturbations_per_eval=16,\n",
    "    show_progress=True\n",
    ").squeeze(0)\n",
    "\n",
    "print('Attribution range:', attrs.min().item(), 'to', attrs.max().item())\n",
    "show_attr(attrs)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "As we can see, the new attribution result removes the chairs and border with the help of Lasso.\n",
    "\n",
    "Another interesting question to explore is if the model also recognizes the chairs in the image. To answer this, we will use the most related label `rocking_chair` from ImageNet as the target, whose label index is `765`. We can check how confident the model feels about the alternative object."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "rocking_chair (765): 0.0048\n"
     ]
    }
   ],
   "source": [
    "alter_label_idx = 765\n",
    "\n",
    "alter_prob = output_probs[alter_label_idx].item()\n",
    "print(f'{idx_to_labels[str(alter_label_idx)]} ({alter_label_idx}):', round(alter_prob, 4))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Then, we will redo the attribution with our Lasso Lime."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Lime attribution: 100%|██████████| 1/1 [00:02<00:00,  2.14s/it]\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Attribution range: -0.1657082438468933 to 1.4231761693954468\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x432 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "attrs = lasso_lime.attribute(\n",
    "    img.unsqueeze(0),\n",
    "    target=alter_label_idx,\n",
    "    feature_mask=feature_mask.unsqueeze(0),\n",
    "    n_samples=2 ** n_interpret_features,\n",
    "    perturbations_per_eval=16,\n",
    "    show_progress=True,\n",
    "    return_input_shape=True,\n",
    ").squeeze(0)\n",
    "\n",
    "print('Attribution range:', attrs.min().item(), 'to', attrs.max().item())\n",
    "show_attr(attrs)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "As shown in the heat map, our ResNet does present the right belief about the chair segment. However, it gets hindered by the television segment in the foreground. This may also explain why the model feels less confident about the chairs than the television."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 1.4 Understand the sampling process"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We have already learned how to use Captum's Lime. This section will additionally dive into the internal sampling process to give interested readers an overview of what happens underneath. The goal of the sampling process is to collect a set of training data for the surrogate model. Every data point consists of three parts: interpretable input, model predicted label, and similarity weight. We will roughly illustrate how Lime achieves each of them behind the scenes.\n",
    "\n",
    "As we mentioned before, Lime samples data from the interpretable space. By default, Lime uses the presence or absence of the given mask groups as interpretable features. In our example, facing the above image of 4 segments, the interpretable representation is therefore a binary vector of 4 values indicating if each segment is present or absent. This is why we know there are only 16 possible interpretable representations and can exhaust them with our `iter_combinations`. Lime will keep calling its `perturb_func` to get the sample interpretable inputs. Let us simulate this step and give us such an interpretable input."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Perturbed interpretable sample: tensor([[1, 1, 0, 1]])\n"
     ]
    }
   ],
   "source": [
    "SAMPLE_INDEX = 13\n",
    "\n",
    "pertubed_genertator = iter_combinations()\n",
    "for _ in range(SAMPLE_INDEX + 1):\n",
    "    sample_interp_inp = next(pertubed_genertator)\n",
    "    \n",
    "print('Perturbed interpretable sample:', sample_interp_inp)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Our input sample `[1, 1, 0, 1]` means the third segment (television) is absent while other three segments stay. \n",
    "\n",
    "In order to find out what the target ImageNet's prediction is for this sample, Lime needs to convert it from interpretable space back to the original example space, i.e., the image space. The transformation takes the original example input and modifies it by setting the features of the absent groups to a baseline value which is `0` by default. The transformation function is called `from_interp_rep_transform` under Lime. We will run it manually here to get the pertubed image input and then visualize what it looks like."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "pertubed_img = lasso_lime.from_interp_rep_transform(\n",
    "    sample_interp_inp,\n",
    "    img.unsqueeze(0),\n",
    "    feature_mask=feature_mask.unsqueeze(0),\n",
    "    baselines=0\n",
    ")\n",
    "\n",
    "# invert the normalization for render\n",
    "invert_norm = T.Normalize(\n",
    "    mean=[-0.485/0.229, -0.456/0.224, -0.406/0.225],\n",
    "    std=[1/0.229, 1/0.224, 1/0.225]\n",
    ")\n",
    "\n",
    "plt.imshow(invert_norm(pertubed_img).squeeze(0).permute(1, 2, 0).numpy())\n",
    "plt.axis('off')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "As shown above, compared with the original image, the absent feature, i.e., the television segment, gets masked in the perturbed image, while the other present features stay unchanged. With the perturbed image, Lime is able to find out the model's prediction. Let us still use \"television\" as our attribution target, so the label of perturbed sample is the value of the model's prediction on \"television\". Just for curiosity, we can also check how the model's prediction changes with the perturbation."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Label of the perturbed sample as Television: tensor(3.2104)\n",
      "\n",
      "Probabilities of the perturbed image\n",
      "jigsaw_puzzle (611): 0.094\n",
      "chest (492): 0.0377\n",
      "laptop (620): 0.0338\n",
      "birdhouse (448): 0.0328\n",
      "ashcan (412): 0.0315\n",
      "\n",
      "television (851): 0.006506193894892931\n"
     ]
    }
   ],
   "source": [
    "perturbed_outputs = resnet(pertubed_img).squeeze(0).detach()\n",
    "sample_label = perturbed_outputs[label_idx.item()]\n",
    "print('Label of the perturbed sample as Television:', sample_label)\n",
    "\n",
    "print('\\nProbabilities of the perturbed image')\n",
    "perturbed_output_probs = F.softmax(perturbed_outputs, dim=0)\n",
    "print_result(perturbed_output_probs, topk=5)\n",
    "print(f'\\ntelevision ({label_idx.item()}):', perturbed_output_probs[label_idx].item())"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Reasonably, our ImageNet no longer feel confident about classifying the image as a television.\n",
    "\n",
    "At last, because Lime focuses on the local interpretability, it will calculate the similarity between the perturbed and original images to reweight the loss of this data point. Note the calculation is based on the input space instead of the interpretable space. This step is simply passing the two image tensors into the given `similarity_func` argument which is the exponential kernel of Euclidean distance in our case."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Sample similarity: 0.9705052174205847\n"
     ]
    }
   ],
   "source": [
    "sample_similarity = exp_eucl_distance(img.unsqueeze(0), pertubed_img, None)\n",
    "print('Sample similarity:', sample_similarity)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "This is basically how Lime create a single training data point of `sample_interp_inp`, `sample_label`, and `sample_similarity`. By repeating this process `n_samples` times, it collects a dataset to train the interpretable model.\n",
    "\n",
    "It is Worth noting that the steps we showed in this section is an example based on our Lime instance configured above. The logic of each step can be customized, especially with `LimeBase` class which will be demonstrated in Section 2."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 2. Text Classification"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "In this section, we will take use of a news subject classification example to demonstrate more customizable functions in Lime. We will train a simple embedding-bag classifier on the AG_NEWS dataset and analyze its understanding of words."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [],
   "source": [
    "from torch import nn\n",
    "from torch.utils.data import DataLoader\n",
    "from torch.utils.data.dataset import random_split\n",
    "from torchtext.datasets import AG_NEWS\n",
    "from torchtext.data.utils import get_tokenizer\n",
    "from torchtext.vocab import Vocab\n",
    "\n",
    "from collections import Counter\n",
    "\n",
    "from IPython.core.display import HTML, display"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 2.1 Load the data and define the model"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "`torchtext` has included the AG_NEWS dataset but since it is only split into train & test, we need to further cut a validation set from the original train split. Then we build the vocabulary of the frequent words based on our train split."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Vocabulary size: 18707\n",
      "Num of classes: 4\n"
     ]
    }
   ],
   "source": [
    "ag_ds = list(AG_NEWS(split='train'))\n",
    "\n",
    "ag_train, ag_val = ag_ds[:100000], ag_ds[100000:]\n",
    "\n",
    "tokenizer = get_tokenizer('basic_english')\n",
    "word_counter = Counter()\n",
    "for (label, line) in ag_train:\n",
    "    word_counter.update(tokenizer(line))\n",
    "voc = Vocab(word_counter, min_freq=10)\n",
    "\n",
    "print('Vocabulary size:', len(voc))\n",
    "\n",
    "num_class = len(set(label for label, _ in ag_train))\n",
    "print('Num of classes:', num_class)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The model we use is composed of an embedding-bag, which averages the word embeddings as the latent text representation, and a final linear layer, which maps the latent vector to the logits. Unconventially, `pytorch`'s embedding-bag does not assume the first dimension is batch. Instead, it requires a flattened vector of indices with an additional offset tensor to mark the starting position of each example. You can refer to its [documentation](https://pytorch.org/docs/stable/generated/torch.nn.EmbeddingBag.html#embeddingbag) for details."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [],
   "source": [
    "class EmbeddingBagModel(nn.Module):\n",
    "    def __init__(self, vocab_size, embed_dim, num_class):\n",
    "        super().__init__()\n",
    "        self.embedding = nn.EmbeddingBag(vocab_size, embed_dim)\n",
    "        self.linear = nn.Linear(embed_dim, num_class)\n",
    "\n",
    "    def forward(self, inputs, offsets):\n",
    "        embedded = self.embedding(inputs, offsets)\n",
    "        return self.linear(embedded)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 2.2 Training and Baseline Classification"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "In order to train our classifier, we need to define a collate function to batch the samples into the tensor fomat required by the embedding-bag and create the interable dataloaders."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [],
   "source": [
    "BATCH_SIZE = 64\n",
    "\n",
    "def collate_batch(batch):\n",
    "    labels = torch.tensor([label - 1 for label, _ in batch]) \n",
    "    text_list = [tokenizer(line) for _, line in batch]\n",
    "    \n",
    "    # flatten tokens across the whole batch\n",
    "    text = torch.tensor([voc[t] for tokens in text_list for t in tokens])\n",
    "    # the offset of each example\n",
    "    offsets = torch.tensor(\n",
    "        [0] + [len(tokens) for tokens in text_list][:-1]\n",
    "    ).cumsum(dim=0)\n",
    "\n",
    "    return labels, text, offsets\n",
    "\n",
    "train_loader = DataLoader(ag_train, batch_size=BATCH_SIZE,\n",
    "                          shuffle=True, collate_fn=collate_batch)\n",
    "val_loader = DataLoader(ag_val, batch_size=BATCH_SIZE,\n",
    "                        shuffle=False, collate_fn=collate_batch)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We will then train our embedding-bag model with the common cross-entropy loss and Adam optimizer. Due to the simplicity of this task, 5 epochs should be enough to give us a stable 90% validation accuracy. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [],
   "source": [
    "EPOCHS = 7\n",
    "EMB_SIZE = 64\n",
    "CHECKPOINT = './models/embedding_bag_ag_news.pt'\n",
    "USE_PRETRAINED = True  # change to False if you want to retrain your own model\n",
    "\n",
    "def train_model(train_loader, val_loader):\n",
    "    model = EmbeddingBagModel(len(voc), EMB_SIZE, num_class)\n",
    "    \n",
    "    loss = nn.CrossEntropyLoss()\n",
    "    optimizer = torch.optim.Adam(model.parameters())\n",
    "    \n",
    "    for epoch in range(1, EPOCHS + 1):      \n",
    "        # training\n",
    "        model.train()\n",
    "        total_acc, total_count = 0, 0\n",
    "        \n",
    "        for idx, (label, text, offsets) in enumerate(train_loader):\n",
    "            optimizer.zero_grad()\n",
    "            predited_label = model(text, offsets)\n",
    "            loss(predited_label, label).backward()\n",
    "            optimizer.step()\n",
    "            total_acc += (predited_label.argmax(1) == label).sum().item()\n",
    "            total_count += label.size(0)\n",
    "\n",
    "            if (idx + 1) % 500 == 0:\n",
    "                print('epoch {:3d} | {:5d}/{:5d} batches | accuracy {:8.3f}'.format(\n",
    "                    epoch, idx + 1, len(train_loader), total_acc / total_count\n",
    "                ))\n",
    "                total_acc, total_count = 0, 0       \n",
    "        \n",
    "        # evaluation\n",
    "        model.eval()\n",
    "        total_acc, total_count = 0, 0\n",
    "\n",
    "        with torch.no_grad():\n",
    "            for label, text, offsets in val_loader:\n",
    "                predited_label = model(text, offsets)\n",
    "                total_acc += (predited_label.argmax(1) == label).sum().item()\n",
    "                total_count += label.size(0)\n",
    "\n",
    "        print('-' * 59)\n",
    "        print('end of epoch {:3d} | valid accuracy {:8.3f} '.format(epoch, total_acc / total_count))\n",
    "        print('-' * 59)\n",
    "    \n",
    "    torch.save(model, CHECKPOINT)\n",
    "    return model\n",
    "        \n",
    "eb_model = torch.load(CHECKPOINT) if USE_PRETRAINED else train_model(train_loader, val_loader)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Now, let us take the following sports news and test how our model performs."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Prediction probability: 0.967\n"
     ]
    }
   ],
   "source": [
    "test_label = 2  # {1: World, 2: Sports, 3: Business, 4: Sci/Tec}\n",
    "test_line = ('US Men Have Right Touch in Relay Duel Against Australia THENS, Aug. 17 '\n",
    "            '- So Michael Phelps is not going to match the seven gold medals won by Mark Spitz. '\n",
    "            'And it is too early to tell if he will match Aleksandr Dityatin, '\n",
    "            'the Soviet gymnast who won eight total medals in 1980.')\n",
    "\n",
    "test_labels, test_text, test_offsets = collate_batch([(test_label, test_line)])\n",
    "\n",
    "probs = F.softmax(eb_model(test_text, test_offsets), dim=1).squeeze(0)\n",
    "print('Prediction probability:', round(probs[test_labels[0]].item(), 4))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Our embedding-bag does successfully identify the above news as sports with pretty high confidence."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 2.3 Inspect the model prediction with Lime"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Finally, it is time to bring back Lime to inspect how the model makes the prediction. However, we will use the more customizable `LimeBase` class this time which is also the low-level implementation powering the `Lime` class we used before. The `Lime` class is opinionated when creating features from perturbed binary interpretable representations. It can only set the \"absence\" features to some baseline values while keeping other \"presence\" features. This is not what we want in this case. For text, the interpretable representation is a binary vector indicating if the word of each position is present or not. The corresponding text input should literally remove the absent words so our embedding-bag can calculate the average embeddings of the left words. Setting them to any baselines will pollute the calculation and moreover, our embedding-bag does not have common baseline tokens like `<padding>` at all. Therefore, we have to use `LimeBase` to customize the conversion logic through the `from_interp_rep_transform` argument.\n",
    "\n",
    "`LimeBase` is not opinionated at all so we have to define every piece manually. Let us talk about them in order:\n",
    "- `forward_func`, the forward function of the model. Notice we cannot pass our model directly since Captum always assumes the first dimension is batch while our embedding-bag requires flattened indices. So we will add the dummy dimension later when calling `attribute` and make a wrapper here to remove the dummy dimension before giving to our model.\n",
    "- `interpretable_model`, the surrogate model. This works the same as we demonstrated in the above image classification example. We also use sklearn linear lasso here.\n",
    "- `similarity_func`, the function calculating the weights for training samples. The most common distance used for texts is the cosine similarity in their latent embedding space. The text inputs are just sequences of token indices, so we have to leverage the trained embedding layer from the model to encode them to their latent vectors. Due to this extra encoding step, we cannot use the util `get_exp_kernel_similarity_function('cosine')` like in the image classification example, which directly calculate the cosine similarity of the given inputs.\n",
    "- `perturb_func`, the function to sample interpretable representations. We present another way to define this argument other than using generator as shown in the above image classification example. Here we directly define a function returning a randomized sample every call. It outputs a binary vector where each token is selected independently and uniformly at random.\n",
    "- `perturb_interpretable_space`, whether perturbed samples are in interpretable space. `LimeBase` also supports sampling in the original input space, but we do not need it in our case.\n",
    "- `from_interp_rep_transform`, the function transforming the perturbed interpretable samples back to the original input space. As explained above, this argument is the main reason for us to use `LimeBase`. We pick the subset of the present tokens from the original text input according to the interpretable representation.\n",
    "- `to_interp_rep_transform`, the opposite of `from_interp_rep_transform`. It is needed only when `perturb_interpretable_space` is set to false."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [],
   "source": [
    "# remove the batch dimension for the embedding-bag model\n",
    "def forward_func(text, offsets):\n",
    "    return eb_model(text.squeeze(0), offsets)\n",
    "\n",
    "# encode text indices into latent representations & calculate cosine similarity\n",
    "def exp_embedding_cosine_distance(original_inp, perturbed_inp, _, **kwargs):\n",
    "    original_emb = eb_model.embedding(original_inp, None)\n",
    "    perturbed_emb = eb_model.embedding(perturbed_inp, None)\n",
    "    distance = 1 - F.cosine_similarity(original_emb, perturbed_emb, dim=1)\n",
    "    return torch.exp(-1 * (distance ** 2) / 2)\n",
    "\n",
    "# binary vector where each word is selected independently and uniformly at random\n",
    "def bernoulli_perturb(text, **kwargs):\n",
    "    probs = torch.ones_like(text) * 0.5\n",
    "    return torch.bernoulli(probs).long()\n",
    "\n",
    "# remove absent token based on the intepretable representation sample\n",
    "def interp_to_input(interp_sample, original_input, **kwargs):\n",
    "    return original_input[interp_sample.bool()].view(original_input.size(0), -1)\n",
    "\n",
    "lasso_lime_base = LimeBase(\n",
    "    forward_func, \n",
    "    interpretable_model=SkLearnLasso(alpha=0.08),\n",
    "    similarity_func=exp_embedding_cosine_distance,\n",
    "    perturb_func=bernoulli_perturb,\n",
    "    perturb_interpretable_space=True,\n",
    "    from_interp_rep_transform=interp_to_input,\n",
    "    to_interp_rep_transform=None\n",
    ")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The attribution call is the same as the `Lime` class. Just remember to add the dummy batch dimension to the text input and put the offsets in the `additional_forward_args` because it is not a feature for the classification but a metadata for the text input."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Lime Base attribution: 100%|██████████| 32000/32000 [00:22<00:00, 1432.67it/s]\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Attribution range: -0.4232264757156372 to 0.9536108374595642\n"
     ]
    }
   ],
   "source": [
    "attrs = lasso_lime_base.attribute(\n",
    "    test_text.unsqueeze(0), # add batch dimension for Captum\n",
    "    target=test_labels,\n",
    "    additional_forward_args=(test_offsets,),\n",
    "    n_samples=32000,\n",
    "    show_progress=True\n",
    ").squeeze(0)\n",
    "\n",
    "print('Attribution range:', attrs.min().item(), 'to', attrs.max().item())"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "At last, let us create a simple visualization to highlight the influential words where green stands for positive correlation and red for negative."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<p><mark style=\"background-color:rgba(255,0,0,0.45640903078960515)\">us</mark> <mark style=\"background-color:rgba(0,255,0,0.0)\">men</mark> <mark style=\"background-color:rgba(0,255,0,0.0)\">have</mark> <mark style=\"background-color:rgba(0,255,0,0.0)\">right</mark> <mark style=\"background-color:rgba(0,255,0,0.0)\">touch</mark> <mark style=\"background-color:rgba(0,255,0,0.0)\">in</mark> <mark style=\"background-color:rgba(0,255,0,0.0)\">relay</mark> <mark style=\"background-color:rgba(255,0,0,0.3798096495636427)\">duel</mark> <mark style=\"background-color:rgba(0,255,0,0.0)\">against</mark> <mark style=\"background-color:rgba(0,255,0,0.0)\">australia</mark> <mark style=\"background-color:rgba(0,255,0,0.9765299982384382)\">thens</mark> <mark style=\"background-color:rgba(0,255,0,0.0)\">,</mark> <mark style=\"background-color:rgba(0,255,0,0.0)\">aug</mark> <mark style=\"background-color:rgba(255,0,0,0.5595067172836139)\">.</mark> <mark style=\"background-color:rgba(0,255,0,0.2644781853030491)\">17</mark> <mark style=\"background-color:rgba(255,0,0,0.6505585874582221)\">-</mark> <mark style=\"background-color:rgba(0,255,0,0.0)\">so</mark> <mark style=\"background-color:rgba(255,0,0,0.5975870827935951)\">michael</mark> <mark style=\"background-color:rgba(0,255,0,0.0)\">phelps</mark> <mark style=\"background-color:rgba(0,255,0,0.0)\">is</mark> <mark style=\"background-color:rgba(0,255,0,0.0)\">not</mark> <mark style=\"background-color:rgba(0,255,0,0.0)\">going</mark> <mark style=\"background-color:rgba(0,255,0,0.0)\">to</mark> <mark style=\"background-color:rgba(0,255,0,0.821556492286908)\">match</mark> <mark style=\"background-color:rgba(0,255,0,0.0)\">the</mark> <mark style=\"background-color:rgba(0,255,0,0.0)\">seven</mark> <mark style=\"background-color:rgba(0,255,0,0.0)\">gold</mark> <mark style=\"background-color:rgba(0,255,0,0.4329777371187277)\">medals</mark> <mark style=\"background-color:rgba(0,255,0,0.12680978752758576)\">won</mark> <mark style=\"background-color:rgba(255,0,0,0.3485568949642219)\">by</mark> <mark style=\"background-color:rgba(0,255,0,0.0)\">mark</mark> <mark style=\"background-color:rgba(0,255,0,0.0)\">spitz</mark> <mark style=\"background-color:rgba(255,0,0,0.5688951988163126)\">.</mark> <mark style=\"background-color:rgba(0,255,0,0.0)\">and</mark> <mark style=\"background-color:rgba(0,255,0,0.0)\">it</mark> <mark style=\"background-color:rgba(0,255,0,0.0)\">is</mark> <mark style=\"background-color:rgba(0,255,0,0.0)\">too</mark> <mark style=\"background-color:rgba(0,255,0,0.0)\">early</mark> <mark style=\"background-color:rgba(0,255,0,0.0)\">to</mark> <mark style=\"background-color:rgba(0,255,0,0.0)\">tell</mark> <mark style=\"background-color:rgba(0,255,0,0.0)\">if</mark> <mark style=\"background-color:rgba(0,255,0,0.5334755337904876)\">he</mark> <mark style=\"background-color:rgba(0,255,0,0.0)\">will</mark> <mark style=\"background-color:rgba(0,255,0,0.8323776168908136)\">match</mark> <mark style=\"background-color:rgba(0,255,0,0.0)\">aleksandr</mark> <mark style=\"background-color:rgba(0,255,0,0.0)\">dityatin</mark> <mark style=\"background-color:rgba(0,255,0,0.0)\">,</mark> <mark style=\"background-color:rgba(0,255,0,0.0)\">the</mark> <mark style=\"background-color:rgba(0,255,0,0.0)\">soviet</mark> <mark style=\"background-color:rgba(0,255,0,0.6241970149184269)\">gymnast</mark> <mark style=\"background-color:rgba(0,255,0,0.0)\">who</mark> <mark style=\"background-color:rgba(0,255,0,0.13470780472922608)\">won</mark> <mark style=\"background-color:rgba(0,255,0,0.3170152619355239)\">eight</mark> <mark style=\"background-color:rgba(0,255,0,0.0)\">total</mark> <mark style=\"background-color:rgba(0,255,0,0.4189161099301892)\">medals</mark> <mark style=\"background-color:rgba(0,255,0,0.0)\">in</mark> <mark style=\"background-color:rgba(0,255,0,0.0)\">1980</mark> <mark style=\"background-color:rgba(255,0,0,0.5665426944946758)\">.</mark></p>"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "def show_text_attr(attrs):\n",
    "    rgb = lambda x: '255,0,0' if x < 0 else '0,255,0'\n",
    "    alpha = lambda x: abs(x) ** 0.5\n",
    "    token_marks = [\n",
    "        f'<mark style=\"background-color:rgba({rgb(attr)},{alpha(attr)})\">{token}</mark>'\n",
    "        for token, attr in zip(tokenizer(test_line), attrs.tolist())\n",
    "    ]\n",
    "    \n",
    "    display(HTML('<p>' + ' '.join(token_marks) + '</p>'))\n",
    "    \n",
    "show_text_attr(attrs)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The above visulization should render something like the image below where the model links the \"Sports\" subject to many reasonable words, like \"match\" and \"medals\".\n",
    "\n",
    "![Lime Text](img/lime_text_viz.png)"
   ]
  }
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